Analysis of variability in activity-travel patterns based on multi-day GPS-imputed travel diaries

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Abstract

This paper addresses the issue of day-to-day variability in activity-travel behavior. First, multidimensional sequence alignment is applied to measure the degree of dissimilarity in individual daily activity-travel sequences between pairs of travel days. Next, a panel effects regression model is used to estimate the effects of socio-demographics and days of the week on the degree of dissimilarity in dayto-day activity-travel sequences. The data on activity-travel patterns were collected using GPS-enabled smartphones and a prompted recall survey instrument. Results show that days of the week have significant effects on the variability in day-to-day activity-travel behavior; the degree of dissimilarity in activity-travel sequences is strongly influenced by respondent socio-demographic profiles; individuals having more control over and more flexibility in their work schedule also show greater intrapersonal variability. The paper ends with a discussion of the limitations of this study and the implications of the research findings for future research.

Original languageEnglish
Title of host publicationProceedings of the 19th International Conference of Hong Kong Society for Transportation Studies, HKSTS 2014 - Transportation and Infrastructure
EditorsZ. Leng, Y. H. Wang
PublisherHong Kong Society for Transportation Studies
Pages341-348
Number of pages8
ISBN (Electronic)9789881581433
Publication statusPublished - 1 Jan 2014
Event19th International Conference of Hong Kong Society for Transportation Studies (HKSTS 2014) - Hong Kong, China
Duration: 13 Dec 201415 Dec 2014

Conference

Conference19th International Conference of Hong Kong Society for Transportation Studies (HKSTS 2014)
Abbreviated titleHKSTS2014
CountryChina
CityHong Kong
Period13/12/1415/12/14
OtherTransportation and Infrastructure

Keywords

  • Activity-travel sequence
  • GPS-enabled smartphone
  • Multi-dimensional sequence alignment
  • Panel effects regression model
  • Variability

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